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Practical Computational Toolkits for Dendrimers and Dendrons Structure Design

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Practical Computational Toolkits for Dendrimers and Dendrons Structure Design Practical computational toolkits for dendrimers and dendrons structure design Nuno Martinho1,2,3, Liana C. Silva1, Helena F. Florindo1, Steve Brocchini2, Teresa Barata2,* and Mire Zloh3,* 1 Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Av. Professor Gama Pinto, Lisbon 1649-003, Portugal 2 Department of Pharmaceutics, UCL School of Pharmacy, University College London, 29/39 Brunswick Square, London WC1N 1AX, UK 3 School of Life and Medical Sciences, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UK * Authors to whom correspondence should be addressed. e-mail: [email protected] & [email protected] ABSTRACT Dendrimers and dendrons offer an excellent platform for developing novel drug delivery systems and medicines. The rational design and further development of these repetitively branched systems are restricted by difficulties in scalable synthesis and structural determination, which can be overcome by judicious use of molecular modelling and molecular simulations. A major difficulty to utilise in silico studies to design dendrimers lies in the laborious generation of their structures. Current modelling tools utilise automated assembly of simpler dendrimers or the inefficient manual assembly of monomer precursors to generate more complicated dendrimer structures. Herein we describe two novel graphical user interface (GUI) toolkits written in Python that provide an improved degree of automation for rapid assembly of dendrimers and generation of their 2D and 3D structures. Our first toolkit uses the RDkit library, SMILES nomenclature of monomers and SMARTS reaction nomenclature to generate SMILES and mol files of dendrimers without 3D coordinates. These files are used for simple graphical representations and storing their structures in databases. The second toolkit assembles complex topology dendrimers from monomers to construct 3D dendrimer structures to be used as starting points for simulation using existing and widely available software and force fields. Both tools were validated for ease-of-use to prototype dendrimer structure and the second toolkit was especially relevant for dendrimers of high complexity and size. INTRODUCTION Dendrimers and dendrons are a type of hyper-branched macromolecules characterised by a well-defined three-dimensional branching architecture with a high degree of mono-disperse molecular weight characteristics emanating from a multifunctional core [1]. They are often defined by the composition and chemistry of their core, branching (internal monomers) and by their multivalent terminal groups (surface groups). This results in a wide diversity of different topologies described in the literature since different core precursor and branching monomers can be used in their preparation. In particular, the use of different types of monomers can have dramatic changes in the size, volume, shape, flexibility, physicochemical properties and available space (interior density) of dendrimers [2, 3]. These features provide an excellent platform for potential applications of dendrimers for various purposes, for example: enhancing solubility and delivery of drugs [4–8], optimization of therapeutic agents toxicity [9, 10], developing sensors [11], diagnostic agents [4] and transfection reagents [12]. The multivalent surface of dendrimers can also be utilized for passive or active targeting by modification of terminal groups using small molecules or macromolecules to employ relevant molecular recognition mechanisms [12–17]. Dendrimers are prepared following a wide range of synthetic routes. Divergent routes essentially proceed from the core outwards, and convergent routes tend to proceed from branched end groups to the core. Due to the hyperbranched character of dendrimers, the size of the structure, complexity and branching increases with each additional generation. The increase of each generation often results in the doubling the number of end groups with the possibility that intricate branched structures can be formed. Eventually dendrimers reach a generation number where end-group crowding results in restricted chemical accessibility self- interruption of synthesis [18]. The conformation of dendrimers at lower generation numbers can be different from higher number generation dendrimers and their conformation in solution is highly dependent on chemical structure and requires analysis on a case-by-case basis. For example, generations 1 and 3 of equilibrated triazine dendrimers in water assume a globular-like configuration with a dense core and flexible surface, generation 5 becomes less spherical but having still dense core, while generations 7 and 9 are porous and open to the penetration to the solvent [19]. As with most polymers, the behaviour of end groups depends on the nature of the terminal groups, in some cases the end groups may be flexible [19] or folded into the interior of the dendrimer [18]. The size and flexibility of structures of many dendrimers prevent the unequivocal determination of their conformation using common experimental techniques. Currently, there are only 15 reported structures of dendrimers determined by X-ray crystallography in the protein data bank (PDB) [20]. There is a significant progress in analysis of dendrimers using NMR from distinguishing the signals of different generations and signal assignments [21, 22]to understanding the dynamics and mobility of dendrimers [23]. However, the full three dimensional structure determination of dendrimers using NMR is still hindered due to the repetitive nature of monomers in each generation of the dendrimer that leads to ambiguous assignments of nOe signals. The use of biophysical and physicochemical techniques can provide information on complexes that dendrimers form with other molecules of interest [24], however the detailed structural information that can be obtained experimentally remains limited. Due to the large variation in chemical structures of monomers that can be used to prepare dendrimers, it is increasingly difficult to envision their important properties, such as shape, flexibility and interior flexibility. Molecular modelling and simulations has become a powerful tool to probe and model molecular structural information. Molecular modelling has been increasingly used to rationally design dendrimers for biomedical applications with special focus on studying their structure and dynamic response to environment stimulus (e.g. pH change) as well as interactions of dendrimers with other molecules [23, 25–28]. Modelling studies of dendrimers have been conducted using different force fields developed for proteins and small molecules, including CHARMM[29], AMBER[30], CVFF[31], Dreiding[32], GROMOS[33], COMPAS [34] and OPLS[35]. Although these types of molecular modelling studies provide information that corroborate experimental data, it still remains difficult to generate the three dimensional models of relevant dendrimers in silico. This is particularly true for larger generations or for non-regular dendrimers or dendrons with complex structures. Several molecular modelling tools are suited to build regular dendrimers and hyper-branched polymers, namely Starmaker (part of Silico toolkit)[36, 37], Dendrimer Building Toolkit[30], Dendrimer Builder in Materials Studio [38] and HBP builder [39]. However, there are still opportunities to automate process of generation of the structures of more complex dendrimers or dendrons. We have previously developed a method to describe dendrimer structures as a sequence of monomers accompanied by a “connectivity table” [40] for use in generating structure using XPLOR-NIH software [41]. This method still required the manual description of the sequence and the “connectivity table” and thus lacked the automation required for general use. Therefore, there is still a demand for a GUI that allows building frameworks of dendrimers and dendrons with different chemistries and being able to use different force fields in a reliable manner. This manuscript concerns the description of an algorithm presented in a GUI to generate the sequence of monomers and connectivity tables to be exported to XPLOR to generate topology files of dendrimers and complete 3D structure to be used in MD simulation packages. Additionally, we also provide an automated method to generate 2D structure and smiles of dendrimers for fast prototyping and database management of these macromolecules. Both tools were shown to provide a faster and easier way to assemble dendrimers in preparation for further computational studies. RESULTS AND DISCUSSION Our approach aims to provide a framework of tools to build dendrimers and dendrons in a reliable and consistent way using two approaches according to the level of parameterization and complexity of the dendrimer required. As with other dendrimer building strategies, the principle is to construct the dendrimer framework from the set of monomers needed to increase the dendrimer generation number. We focused on tools written in Python language that allow the design of different chemistry templates with varying complexity. In cases where parameterization for further MD simulation of dendrimers is not required and only the assembly is important we provide a GUI to generate 2D mol files of dendrimers (Toolkit 1). When parameterization is required to further model the dendrimers, we created a GUI to automate our previously reported method [40]. This new GUI generates the input file containing the sequence of monomers and their connectivity to
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